cs.AI - 人工智能
cs.CL - 计算与语言 cs.CV - 机器视觉与模式识别 cs.CY - 计算与社会 cs.DC - 分布式、并行与集群计算 cs.IR - 信息检索 cs.IT - 信息论 cs.LG - 自动学习 cs.LO - 计算逻辑 cs.MA - 多代理系统 cs.NE - 神经与进化计算 cs.NI - 网络和互联网体系结构 cs.PL - 编程语言 cs.RO - 机器人学 cs.SI - 社交网络与信息网络 eess.IV - 图像与视频处理 eess.SP - 信号处理 math.OC - 优化与控制 math.ST - 统计理论 physics.comp-ph - 计算物理学 physics.soc-ph - 物理学与社会 q-bio.PE - 人口与发展 stat.AP - 应用统计 stat.ME - 统计方法论 stat.ML - (统计)机器学习
• [cs.AI]Conditional LSTM-GAN for Melody Generation from Lyrics
• [cs.AI]Evaluating Empathy in Artificial Agents
• [cs.AI]Playing a Strategy Game with Knowledge-Based Reinforcement Learning
• [cs.AI]Reward Tampering Problems and Solutions in Reinforcement Learning: A Causal Influence Diagram Perspective
• [cs.AI]Tracing Player Knowledge in a Parallel Programming Educational Game
• [cs.CL]A Multi-Type Multi-Span Network for Reading Comprehension that Requires Discrete Reasoning
• [cs.CL]A Multivariate Model for Representing Semantic Non-compositionality
• [cs.CL]Feature-Less End-to-End Nested Term Extraction
• [cs.CL]Multi-Task Self-Supervised Learning for Disfluency Detection
• [cs.CL]Multi-class Hierarchical Question Classification for Multiple Choice Science Exams
• [cs.CL]Raw-to-End Name Entity Recognition in Social Media
• [cs.CL]SenseBERT: Driving Some Sense into BERT
• [cs.CL]Towards End-to-End Learning for Efficient Dialogue Agent by Modeling Looking-ahead Ability
• [cs.CL]Towards Knowledge-Based Recommender Dialog System
• [cs.CL]Visualizing and Understanding the Effectiveness of BERT
• [cs.CL]What’s Wrong with Hebrew NLP? And How to Make it Right
• [cs.CL]X-WikiRE: A Large, Multilingual Resource for Relation Extraction as Machine Comprehension
• [cs.CL]XCMRC: Evaluating Cross-lingual Machine Reading Comprehension
• [cs.CV]3D Human Pose Estimation under limited supervision using Metric Learning
• [cs.CV]A Single-Shot Arbitrarily-Shaped Text Detector based on Context Attended Multi-Task Learning
• [cs.CV]Accelerated CNN Training Through Gradient Approximation
• [cs.CV]Beyond Cartesian Representations for Local Descriptors
• [cs.CV]Conv-MCD: A Plug-and-Play Multi-task Module for Medical Image Segmentation
• [cs.CV]Deep learning for Plankton and Coral Classification
• [cs.CV]Dual Adversarial Inference for Text-to-Image Synthesis
• [cs.CV]FastPose: Towards Real-time Pose Estimation and Tracking via Scale-normalized Multi-task Networks
• [cs.CV]Improved Mix-up with KL-Entropy for Learning From Noisy Labels
• [cs.CV]IoU-balanced Loss Functions for Single-stage Object Detection
• [cs.CV]Learning Trajectory Dependencies for Human Motion Prediction
• [cs.CV]PS^2-Net: A Locally and Globally Aware Network for Point-Based Semantic Segmentation
• [cs.CV]R3Det: Refined Single-Stage Detector with Feature Refinement for Rotating Object
• [cs.CV]SFSegNet: Parse Freehand Sketches using Deep Fully Convolutional Networks
• [cs.CV]To complete or to estimate, that is the question: A Multi-Task Approach to Depth Completion and Monocular Depth Estimation
• [cs.CV]Unpaired Cross-lingual Image Caption Generation with Self-Supervised Rewards
• [cs.CY]A blockchain-based user-centric emission monitoring and trading system for multi-modal mobility
• [cs.CY]Producers of Popular Science Web Videos. Between New Professionalism and Old Gender Issues
• [cs.DC]Secure Coded Cooperative Computation at the Heterogeneous Edge against Byzantine Attacks
• [cs.IR]CUPCF: Combining Users Preferences in Collaborative Filtering for Better Recommendation
• [cs.IR]FCNHSMRA_HRS: Improve the performance of the movie hybrid recommender system using resource allocation approach
• [cs.IR]Generative Question Refinement with Deep Reinforcement Learning in Retrieval-based QA System
• [cs.IR]GraphSW: a training protocol based on stage-wise training for GNN-based Recommender Model
• [cs.IR]Hamming Sentence Embeddings for Information Retrieval
• [cs.IR]SHREWD: Semantic Hierarchy-based Relational Embeddings for Weakly-supervised Deep Hashing
• [cs.IR]Two-stage Federated Phenotyping and Patient Representation Learning
• [cs.IT]Diffusive Mobile MC with Absorbing Receivers: Stochastic Analysis and Applications
• [cs.IT]Ergodic Rate Analysis of Cooperative Ambient Backscatter Communication
• [cs.IT]Generalized Haar condition-based phaseless random sampling for compactly supported functions in shift-invariant spaces
• [cs.IT]Non-coherent Detection and Bit Error Rate for an Ambient Backscatter Link in Time-Selective Fading
• [cs.LG]Adaptive Regularization of Labels
• [cs.LG]Distinction Maximization Loss: Fast, Scalable, Turnkey, and Native Neural Networks Out-of-Distribution Detection simply by Replacing the SoftMax Loss
• [cs.LG]Domain-adversarial Network Alignment
• [cs.LG]From Crystallized Adaptivity to Fluid Adaptivity in Deep Reinforcement Learning — Insights from Biological Systems on Adaptive Flexibility
• [cs.LG]HONEM: Network Embedding Using Higher-Order Patterns in Sequential Data
• [cs.LG]Improving Randomized Learning of Feedforward Neural Networks by Appropriate Generation of Random Parameters
• [cs.LG]Learning Credible Deep Neural Networks with Rationale Regularization
• [cs.LG]Mapping State Space using Landmarks for Universal Goal Reaching
• [cs.LG]PHYRE: A New Benchmark for Physical Reasoning
• [cs.LG]Predicting Eating Events in Free Living Individuals — A Technical Report
• [cs.LG]Resonant Machine Learning Based on Complex Growth Transform Dynamical Systems
• [cs.LG]Sex Trafficking Detection with Ordinal Regression Neural Networks
• [cs.LG]Temporal Collaborative Ranking Via Personalized Transformer
• [cs.LG]Towards Automated Machine Learning: Evaluation and Comparison of AutoML Approaches and Tools
• [cs.LO]Shield Synthesis for Real: Enforcing Safety in Cyber-Physical Systems
• [cs.LO]Vector spaces as Kripke frames
• [cs.MA]Massive Multi-Agent Data-Driven Simulations of the GitHub Ecosystem
• [cs.NE]MOEA/D with Uniformly Randomly Adaptive Weights
• [cs.NI]Distributed Rate Control in Downlink NOMA Networks with Reliability Constraints
• [cs.PL]CLOTHO: Directed Test Generation for Weakly Consistent Database Systems
• [cs.RO]Comparing Metrics for Robustness Against External Perturbations in Dynamic Trajectory Optimization
• [cs.RO]Distributed Path Planning for Executing Cooperative Tasks with Time Windows
• [cs.RO]Learning Interactive Behaviors for Musculoskeletal Robots Using Bayesian Interaction Primitives
• [cs.RO]Sample-efficient Deep Reinforcement Learning with Imaginary Rollouts for Human-Robot Interaction
• [cs.SI]On Gossip-based Information Dissemination in Pervasive Recommender Systems
• [cs.SI]When Your Friends Become Sellers: An Empirical Study of Social Commerce Site Beidian
• [eess.IV]A Multimodal Vision Sensor for Autonomous Driving
• [eess.IV]A deep learning model for segmentation of geographic atrophy to study its long-term natural history
• [eess.IV]Automated Rib Fracture Detection of Postmortem Computed Tomography Images Using Machine Learning Techniques
• [eess.IV]Bayesian Generative Models for Knowledge Transfer in MRI Semantic Segmentation Problems
• [eess.IV]Deep Slice Interpolation via Marginal Super-Resolution, Fusion and Refinement
• [eess.IV]Graph Convolutional Networks for Coronary Artery Segmentation in Cardiac CT Angiography
• [eess.IV]Multimodal Volume-Aware Detection and Segmentation for Brain Metastases Radiosurgery
• [eess.IV]Recognition of Ischaemia and Infection in Diabetic Foot Ulcers: Dataset and Techniques
• [eess.IV]Towards multi-sequence MR image recovery from undersampled k-space data
• [eess.SP]On the Age of Information of Short-Packet Communications with Packet Management
• [math.OC]Distributionally Robust Optimization: A Review
• [math.ST]Efficient Estimation of Pathwise Differentiable Target Parameters with the Undersmoothed Highly Adaptive Lasso
• [math.ST]Exponential two-armed bandit problem
• [math.ST]Robust One-Bit Recovery via ReLU Generative Networks: Improved Statistical Rates and Global Landscape Analysis
• [math.ST]The generalization error of random features regression: Precise asymptotics and double descent curve
• [physics.comp-ph]Cosmological N-body simulations: a challenge for scalable generative models
• [physics.soc-ph]Deep reinforcement learning in World-Earth system models to discover sustainable management strategies
• [q-bio.PE]Deep learning on butterfly phenotypes tests evolution’s oldest mathematical model
• [q-bio.PE]Epidemic models on social networks — with inference
• [stat.AP]A hierarchical model for estimating exposure-response curves from multiple studies
• [stat.AP]Learning Signal Subgraphs from Longitudinal Brain Networks with Symmetric Bilinear Logistic Regression
• [stat.AP]Robust parametric modeling of Alzheimer’s disease progression
• [stat.ME]A grouped, selectively weighted false discovery rate procedure
• [stat.ME]A hypothesis test of feasibility for external pilot trials assessing recruitment, follow-up and adherence rates
• [stat.ME]False Discovery Rate for Functional Data
• [stat.ME]With Malice Towards None: Assessing Uncertainty via Equalized Coverage
• [stat.ML]A Bayesian Choice Model for Eliminating Feedback Loops
• [stat.ML]Combining Prediction Intervals on Multi-Source Non-Disclosed Regression Datasets
• [stat.ML]End-to-End Learning from Complex Multigraphs with Latent Graph Convolutional Networks
• [stat.ML]Maximum Relevance and Minimum Redundancy Feature Selection Methods for a Marketing Machine Learning Platform
• [stat.ML]Mixed pooling of seasonality in time series pallet forecasting
• [stat.ML]Optimizing Ensemble Weights and Hyperparameters of Machine Learning Models for Regression Problems
• [stat.ML]Sequential Computer Experimental Design for Estimating an Extreme Probability or Quantile
• [stat.ML]Uplift Modeling for Multiple Treatments with Cost Optimization
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• [cs.AI]Conditional LSTM-GAN for Melody Generation from Lyrics
Yi Yu, Simon Canales
http://arxiv.org/abs/1908.05551v1
• [cs.AI]Evaluating Empathy in Artificial Agents
Özge Nilay Yalçın
http://arxiv.org/abs/1908.05341v1
• [cs.AI]Playing a Strategy Game with Knowledge-Based Reinforcement Learning
Viktor Voss, Liudmyla Nechepurenko, Dr. Rudi Schaefer, Steffen Bauer
http://arxiv.org/abs/1908.05472v1
• [cs.AI]Reward Tampering Problems and Solutions in Reinforcement Learning: A Causal Influence Diagram Perspective
Tom Everitt, Marcus Hutter
http://arxiv.org/abs/1908.04734v2
• [cs.AI]Tracing Player Knowledge in a Parallel Programming Educational Game
Pavan Kantharaju, Katelyn Alderfer, Jichen Zhu, Bruce Char, Brian Smith, Santiago Ontañón
http://arxiv.org/abs/1908.05632v1
• [cs.CL]A Multi-Type Multi-Span Network for Reading Comprehension that Requires Discrete Reasoning
Minghao Hu, Yuxing Peng, Zhen Huang, Dongsheng Li
http://arxiv.org/abs/1908.05514v1
• [cs.CL]A Multivariate Model for Representing Semantic Non-compositionality
Meghdad Farahmand
http://arxiv.org/abs/1908.05490v1
• [cs.CL]Feature-Less End-to-End Nested Term Extraction
Yuze Gao, Yu Yuan
http://arxiv.org/abs/1908.05426v1
• [cs.CL]Multi-Task Self-Supervised Learning for Disfluency Detection
Shaolei Wang, Wanxiang Che, Qi Liu, Pengda Qin, Ting Liu, William Yang Wang
http://arxiv.org/abs/1908.05378v1
• [cs.CL]Multi-class Hierarchical Question Classification for Multiple Choice Science Exams
Dongfang Xu, Peter Jansen, Jaycie Martin, Zhengnan Xie, Vikas Yadav, Harish Tayyar Madabushi, Oyvind Tafjord, Peter Clark
http://arxiv.org/abs/1908.05441v1
• [cs.CL]Raw-to-End Name Entity Recognition in Social Media
Liyuan Liu, Zihan Wang, Jingbo Shang, Dandong Yin, Heng Ji, Xiang Ren, Shaowen Wang, Jiawei Han
http://arxiv.org/abs/1908.05344v1
• [cs.CL]SenseBERT: Driving Some Sense into BERT
Yoav Levine, Barak Lenz, Or Dagan, Dan Padnos, Or Sharir, Shai Shalev-Shwartz, Amnon Shashua, Yoav Shoham
http://arxiv.org/abs/1908.05646v1
• [cs.CL]Towards End-to-End Learning for Efficient Dialogue Agent by Modeling Looking-ahead Ability
Zhuoxuan Jiang, Xian-Ling Mao, Ziming Huang, Jie Ma, Shaochun Li
http://arxiv.org/abs/1908.05408v1
• [cs.CL]Towards Knowledge-Based Recommender Dialog System
Qibin Chen, Junyang Lin, Yichang Zhang, Ming Ding, Yukuo Cen, Hongxia Yang, Jie Tang
http://arxiv.org/abs/1908.05391v1
• [cs.CL]Visualizing and Understanding the Effectiveness of BERT
Yaru Hao, Li Dong, Furu Wei, Ke Xu
http://arxiv.org/abs/1908.05620v1
• [cs.CL]What’s Wrong with Hebrew NLP? And How to Make it Right
Reut Tsarfaty, Amit Seker, Shoval Sadde, Stav Klein
http://arxiv.org/abs/1908.05453v1
• [cs.CL]X-WikiRE: A Large, Multilingual Resource for Relation Extraction as Machine Comprehension
Mostafa Abdou, Cezar Sas, Rahul Aralikatte, Isabelle Augenstein, Anders Søgaard
http://arxiv.org/abs/1908.05111v2
• [cs.CL]XCMRC: Evaluating Cross-lingual Machine Reading Comprehension
Pengyuan Liu, Yuning Deng, Chenghao Zhu, Han Hu
http://arxiv.org/abs/1908.05416v1
• [cs.CV]3D Human Pose Estimation under limited supervision using Metric Learning
Rahul Mitra, Nitesh B. Gundavarapu, Sudharshan Chandra Babu, Prashasht Bindal, Abhishek Sharma, Arjun Jain
http://arxiv.org/abs/1908.05293v1
• [cs.CV]A Single-Shot Arbitrarily-Shaped Text Detector based on Context Attended Multi-Task Learning
Pengfei Wang, Chengquan Zhang, Fei Qi, Zuming Huang, Mengyi En, Junyu Han, Jingtuo Liu, Errui Ding, Guangming Shi
http://arxiv.org/abs/1908.05498v1
• [cs.CV]Accelerated CNN Training Through Gradient Approximation
Ziheng Wang, Sree Harsha Nelaturu
http://arxiv.org/abs/1908.05460v1
• [cs.CV]Beyond Cartesian Representations for Local Descriptors
Patrick Ebel, Anastasiia Mishchuk, Kwang Moo Yi, Pascal Fua, Eduard Trulls
http://arxiv.org/abs/1908.05547v1
• [cs.CV]Conv-MCD: A Plug-and-Play Multi-task Module for Medical Image Segmentation
Balamurali Murugesan, Kaushik Sarveswaran, Sharath M Shankaranarayana, Keerthi Ram, Jayaraj Joseph, Mohanasankar Sivaprakasam
http://arxiv.org/abs/1908.05311v1
• [cs.CV]Deep learning for Plankton and Coral Classification
Alessandra Lumini, Loris Nanni, Gianluca Maguolo
http://arxiv.org/abs/1908.05489v1
• [cs.CV]Dual Adversarial Inference for Text-to-Image Synthesis
Qicheng Lao, Mohammad Havaei, Ahmad Pesaranghader, Francis Dutil, Lisa Di Jorio, Thomas Fevens
http://arxiv.org/abs/1908.05324v1
• [cs.CV]FastPose: Towards Real-time Pose Estimation and Tracking via Scale-normalized Multi-task Networks
Jiabin Zhang, Zheng Zhu, Wei Zou, Peng Li, Yanwei Li, Hu Su, Guan Huang
http://arxiv.org/abs/1908.05593v1
• [cs.CV]Improved Mix-up with KL-Entropy for Learning From Noisy Labels
Qian Zhang, Feifei Lee, Ya-Gang Wang, Qiu Chen
http://arxiv.org/abs/1908.05488v1
• [cs.CV]IoU-balanced Loss Functions for Single-stage Object Detection
Shengkai Wu, Xiaoping Li
http://arxiv.org/abs/1908.05641v1
• [cs.CV]Learning Trajectory Dependencies for Human Motion Prediction
Wei Mao, Miaomiao Liu, Mathieu Salzmann, Hongdong Li
http://arxiv.org/abs/1908.05436v1
• [cs.CV]PS^2-Net: A Locally and Globally Aware Network for Point-Based Semantic Segmentation
Na Zhao, Tat-Seng Chua, Gim Hee Lee
http://arxiv.org/abs/1908.05425v1
• [cs.CV]R3Det: Refined Single-Stage Detector with Feature Refinement for Rotating Object
Xue Yang, Qingqing Liu, Junchi Yan, Ang Li
http://arxiv.org/abs/1908.05612v1
• [cs.CV]SFSegNet: Parse Freehand Sketches using Deep Fully Convolutional Networks
Junkun Jiang, Ruomei Wang, Shujin Lin, Fei Wang
http://arxiv.org/abs/1908.05389v1
• [cs.CV]To complete or to estimate, that is the question: A Multi-Task Approach to Depth Completion and Monocular Depth Estimation
Amir Atapour-Abarghouei, Toby P. Breckon
http://arxiv.org/abs/1908.05540v1
• [cs.CV]Unpaired Cross-lingual Image Caption Generation with Self-Supervised Rewards
Yuqing Song, Shizhe Chen, Yida Zhao, Qin Jin
http://arxiv.org/abs/1908.05407v1
• [cs.CY]A blockchain-based user-centric emission monitoring and trading system for multi-modal mobility
Johannes Eckert, David López, Carlos Lima Azevedo, Bilal Farooq
http://arxiv.org/abs/1908.05629v1
• [cs.CY]Producers of Popular Science Web Videos. Between New Professionalism and Old Gender Issues
Jesus Munoz Morcillo, Klemens Czurda, Andrea Geipel, Caroline Y. Robertson-von Trotha
http://arxiv.org/abs/1908.05572v1
• [cs.DC]Secure Coded Cooperative Computation at the Heterogeneous Edge against Byzantine Attacks
Yasaman Keshtkarjahromi, Rawad Bitar, Venkat Dasari, Salim El Rouayheb, Hulya Seferoglu
http://arxiv.org/abs/1908.05385v1
• [cs.IR]CUPCF: Combining Users Preferences in Collaborative Filtering for Better Recommendation
Mostafa Khalaji, Nilufar Mohammadnejad
http://arxiv.org/abs/1908.05609v1
• [cs.IR]FCNHSMRA_HRS: Improve the performance of the movie hybrid recommender system using resource allocation approach
Mostafa Khalaji, Nilufar Mohammadnejad
http://arxiv.org/abs/1908.05608v1
• [cs.IR]Generative Question Refinement with Deep Reinforcement Learning in Retrieval-based QA System
Ye Liu, Chenwei Zhang, Xiaohui Yan, Yi Chang, Philip S. Yu
http://arxiv.org/abs/1908.05604v1
• [cs.IR]GraphSW: a training protocol based on stage-wise training for GNN-based Recommender Model
Chang-You Tai, Meng-Ru Wu, Yun-Wei Chu, Shao-Yu Chu
http://arxiv.org/abs/1908.05611v1
• [cs.IR]Hamming Sentence Embeddings for Information Retrieval
Felix Hamann, Nadja Kurz, Adrian Ulges
http://arxiv.org/abs/1908.05541v1
• [cs.IR]SHREWD: Semantic Hierarchy-based Relational Embeddings for Weakly-supervised Deep Hashing
Heikki Arponen, Tom E Bishop
http://arxiv.org/abs/1908.05602v1
• [cs.IR]Two-stage Federated Phenotyping and Patient Representation Learning
Dianbo Liu, Dmitriy Dligach, Timothy Miller
http://arxiv.org/abs/1908.05596v1
• [cs.IT]Diffusive Mobile MC with Absorbing Receivers: Stochastic Analysis and Applications
Trang Ngoc Cao, Arman Ahmadzadeh, Vahid Jamali, Wayan Wicke, Phee Lep Yeoh, Jamie Evans, Robert Schober
http://arxiv.org/abs/1908.05600v1
• [cs.IT]Ergodic Rate Analysis of Cooperative Ambient Backscatter Communication
Shaoqing Zhou, Wei Xu, Kezhi Wang, Cunhua Pan, Mohamed-Slim Alouini, Arumugam Nallanathan
http://arxiv.org/abs/1908.05455v1
• [cs.IT]Generalized Haar condition-based phaseless random sampling for compactly supported functions in shift-invariant spaces
Youfa Li, Wenchang Sun
http://arxiv.org/abs/1908.05423v1
• [cs.IT]Non-coherent Detection and Bit Error Rate for an Ambient Backscatter Link in Time-Selective Fading
J. Kartheek Devineni, Harpreet S. Dhillon
http://arxiv.org/abs/1908.05657v1
• [cs.LG]Adaptive Regularization of Labels
Qianggang Ding, Sifan Wu, Hao Sun, Jiadong Guo, Shu-Tao Xia
http://arxiv.org/abs/1908.05474v1
• [cs.LG]Distinction Maximization Loss: Fast, Scalable, Turnkey, and Native Neural Networks Out-of-Distribution Detection simply by Replacing the SoftMax Loss
David Macêdo
http://arxiv.org/abs/1908.05569v1
• [cs.LG]Domain-adversarial Network Alignment
Huiting Hong, Xin Li, Yuangang Pan, Ivor Tsang
http://arxiv.org/abs/1908.05429v1
• [cs.LG]From Crystallized Adaptivity to Fluid Adaptivity in Deep Reinforcement Learning — Insights from Biological Systems on Adaptive Flexibility
Malte Schilling, Helge Ritter, Frank W. Ohl
http://arxiv.org/abs/1908.05348v1
• [cs.LG]HONEM: Network Embedding Using Higher-Order Patterns in Sequential Data
Mandana Saebi, Giovanni Luca Ciampaglia, Lance M Kaplan, Nitesh V Chawla
http://arxiv.org/abs/1908.05387v1
• [cs.LG]Improving Randomized Learning of Feedforward Neural Networks by Appropriate Generation of Random Parameters
Grzegorz Dudek
http://arxiv.org/abs/1908.05542v1
• [cs.LG]Learning Credible Deep Neural Networks with Rationale Regularization
Mengnan Du, Ninghao Liu, Fan Yang, Xia Hu
http://arxiv.org/abs/1908.05601v1
• [cs.LG]Mapping State Space using Landmarks for Universal Goal Reaching
Zhiao Huang, Fangchen Liu, Hao Su
http://arxiv.org/abs/1908.05451v1
• [cs.LG]PHYRE: A New Benchmark for Physical Reasoning
Anton Bakhtin, Laurens van der Maaten, Justin Johnson, Laura Gustafson, Ross Girshick
http://arxiv.org/abs/1908.05656v1
• [cs.LG]Predicting Eating Events in Free Living Individuals — A Technical Report
Jiayi Wang, Jiue-An Yang, Supun Nakandala, Arun Kumar, Marta M. Jankowska
http://arxiv.org/abs/1908.05304v1
• [cs.LG]Resonant Machine Learning Based on Complex Growth Transform Dynamical Systems
Oindrila Chatterjee, Shantanu Chakrabartty
http://arxiv.org/abs/1908.05377v1
• [cs.LG]Sex Trafficking Detection with Ordinal Regression Neural Networks
Longshaokan Wang, Eric Laber, Yeng Saanchi, Sherrie Caltagirone
http://arxiv.org/abs/1908.05434v1
• [cs.LG]Temporal Collaborative Ranking Via Personalized Transformer
Liwei Wu, Shuqing Li, Cho-Jui Hsieh, James Sharpnack
http://arxiv.org/abs/1908.05435v1
• [cs.LG]Towards Automated Machine Learning: Evaluation and Comparison of AutoML Approaches and Tools
Anh Truong, Austin Walters, Jeremy Goodsitt, Keegan Hines, Bayan Bruss, Reza Farivar
http://arxiv.org/abs/1908.05557v1
• [cs.LO]Shield Synthesis for Real: Enforcing Safety in Cyber-Physical Systems
Meng Wu, Jingbo Wang, Jyotirmoy Deshmukh, Chao Wang
http://arxiv.org/abs/1908.05402v1
• [cs.LO]Vector spaces as Kripke frames
Giuseppe Greco, Fei Liang, Michael Moortgat, Alessandra Palmigiano
http://arxiv.org/abs/1908.05528v1
• [cs.MA]Massive Multi-Agent Data-Driven Simulations of the GitHub Ecosystem
Jim Blythe, John Bollenbacher, Di Huang, Pik-Mai Hui, Rachel Krohn, Diogo Pacheco, Goran Muric, Anna Sapienza, Alexey Tregubov, Yong-Yeol Ahn, Alessandro Flammini, Kristina Lerman, Filippo Menczer, Tim Weninger, Emilio Ferrara
http://arxiv.org/abs/1908.05437v1
• [cs.NE]MOEA/D with Uniformly Randomly Adaptive Weights
Lucas R. C. de Farias, Pedro H. M. Braga, Hansenclever F. Bassani, Aluizio F. R. Araújo
http://arxiv.org/abs/1908.05383v1
• [cs.NI]Distributed Rate Control in Downlink NOMA Networks with Reliability Constraints
Onel L. A. López, Hirley Alves, Matti Latva-aho
http://arxiv.org/abs/1908.05513v1
• [cs.PL]CLOTHO: Directed Test Generation for Weakly Consistent Database Systems
Kia Rahmani, Kartik Nagar, Benjamin Delaware, Suresh Jagannathan
http://arxiv.org/abs/1908.05655v1
• [cs.RO]Comparing Metrics for Robustness Against External Perturbations in Dynamic Trajectory Optimization
Henrique Ferrolho, Wolfgang Merkt, Carlo Tiseo, Sethu Vijayakumar
http://arxiv.org/abs/1908.05380v1
• [cs.RO]Distributed Path Planning for Executing Cooperative Tasks with Time Windows
Raghavendra Bhat, Yasin Yazicioglu, Derya Aksaray
http://arxiv.org/abs/1908.05630v1
• [cs.RO]Learning Interactive Behaviors for Musculoskeletal Robots Using Bayesian Interaction Primitives
Joseph Campbell, Arne Hitzmann, Simon Stepputtis, Shuhei Ikemoto, Koh Hosoda, Heni Ben Amor
http://arxiv.org/abs/1908.05552v1
• [cs.RO]Sample-efficient Deep Reinforcement Learning with Imaginary Rollouts for Human-Robot Interaction
Mohammad Thabet, Massimiliano Patacchiola, Angelo Cangelosi
http://arxiv.org/abs/1908.05546v1
• [cs.SI]On Gossip-based Information Dissemination in Pervasive Recommender Systems
Tobias Eichinger, Felix Beierle, Robin Papke, Lucas Rebscher, Hong Chinh Tran, Magdalena Trzeciak
http://arxiv.org/abs/1908.05544v1
• [cs.SI]When Your Friends Become Sellers: An Empirical Study of Social Commerce Site Beidian
Hancheng Cao, Zhilong Chen, Fengli Xu, Tao Wang, Yujian Xu, Lianglun Zhang, Yong Li
http://arxiv.org/abs/1908.05409v1
• [eess.IV]A Multimodal Vision Sensor for Autonomous Driving
Dongming Sun, Xiao Huang, Kailun Yang
http://arxiv.org/abs/1908.05649v1
• [eess.IV]A deep learning model for segmentation of geographic atrophy to study its long-term natural history
Bart Liefers, Johanna M. Colijn, Cristina González-Gonzalo, Timo Verzijden, Paul Mitchell, Carel B. Hoyng, Bram van Ginneken, Caroline C. W. Klaver, Clara I. Sánchez
http://arxiv.org/abs/1908.05621v1
• [eess.IV]Automated Rib Fracture Detection of Postmortem Computed Tomography Images Using Machine Learning Techniques
Samuel Gunz, Svenja Erne, Eric J. Rawdon, Garyfalia Ampanozi, Till Sieberth, Raffael Affolter, Lars C. Ebert, Akos Dobay
http://arxiv.org/abs/1908.05467v1
• [eess.IV]Bayesian Generative Models for Knowledge Transfer in MRI Semantic Segmentation Problems
Anna Kuzina, Evgenii Egorov, Evgeny Burnaev
http://arxiv.org/abs/1908.05480v1
• [eess.IV]Deep Slice Interpolation via Marginal Super-Resolution, Fusion and Refinement
Cheng Peng, Wei-An Lin, Haofu Liao, Rama Chellappa, S. Kevin Zhou
http://arxiv.org/abs/1908.05599v1
• [eess.IV]Graph Convolutional Networks for Coronary Artery Segmentation in Cardiac CT Angiography
Jelmer M. Wolterink, Tim Leiner, Ivana Išgum
http://arxiv.org/abs/1908.05343v1
• [eess.IV]Multimodal Volume-Aware Detection and Segmentation for Brain Metastases Radiosurgery
Szu-Yeu Hu, Wei-Hung Weng, Shao-Lun Lu, Yueh-Hung Cheng, Furen Xiao, Feng-Ming Hsu, Jen-Tang Lu
http://arxiv.org/abs/1908.05418v1
• [eess.IV]Recognition of Ischaemia and Infection in Diabetic Foot Ulcers: Dataset and Techniques
Manu Goyal, Neil Reeves, Satyan Rajbhandari, Naseer Ahmad, Chuan Wang, Moi Hoon Yap
http://arxiv.org/abs/1908.05317v1
• [eess.IV]Towards multi-sequence MR image recovery from undersampled k-space data
Cheng Peng, Wei-An Lin, Rama Chellappa, S. Kevin Zhou
http://arxiv.org/abs/1908.05615v1
• [eess.SP]On the Age of Information of Short-Packet Communications with Packet Management
Rui Wang, Yifan Gu, He Chen, Yonghui Li, Branka Vucetic
http://arxiv.org/abs/1908.05447v1
• [math.OC]Distributionally Robust Optimization: A Review
Hamed Rahimian, Sanjay Mehrotra
http://arxiv.org/abs/1908.05659v1
• [math.ST]Efficient Estimation of Pathwise Differentiable Target Parameters with the Undersmoothed Highly Adaptive Lasso
Mark J. van der Laan, David Benkeser, Weixin Cai
http://arxiv.org/abs/1908.05607v1
• [math.ST]Exponential two-armed bandit problem
Alexander Kolnogorov, Denis Grunev
http://arxiv.org/abs/1908.05531v1
• [math.ST]Robust One-Bit Recovery via ReLU Generative Networks: Improved Statistical Rates and Global Landscape Analysis
Shuang Qiu, Xiaohan Wei, Zhuoran Yang
http://arxiv.org/abs/1908.05368v1
• [math.ST]The generalization error of random features regression: Precise asymptotics and double descent curve
Song Mei, Andrea Montanari
http://arxiv.org/abs/1908.05355v1
• [physics.comp-ph]Cosmological N-body simulations: a challenge for scalable generative models
Nathanaël Perraudin, Ankit Srivastava, Aurelien Lucchi, Tomasz Kacprzak, Thomas Hofmann, Alexandre Réfrégier
http://arxiv.org/abs/1908.05519v1
• [physics.soc-ph]Deep reinforcement learning in World-Earth system models to discover sustainable management strategies
Felix M. Strnad, Wolfram Barfuss, Jonathan F. Donges, Jobst Heitzig
http://arxiv.org/abs/1908.05567v1
• [q-bio.PE]Deep learning on butterfly phenotypes tests evolution’s oldest mathematical model
Jennifer F. Hoyal Cuthill, Nicholas Guttenberg, Sophie Ledger, Robyn Crowther, Blanca Huertas
http://arxiv.org/abs/1908.05635v1
• [q-bio.PE]Epidemic models on social networks — with inference
Tom Britton
http://arxiv.org/abs/1908.05517v1
• [stat.AP]A hierarchical model for estimating exposure-response curves from multiple studies
Joshua P. Keller, Joanne Katz, Amid K. Pokhrel, Michael N. Bates, James Tielsch, Scott L. Zeger
http://arxiv.org/abs/1908.05340v1
• [stat.AP]Learning Signal Subgraphs from Longitudinal Brain Networks with Symmetric Bilinear Logistic Regression
Lu Wang, Zhengwu Zhang
http://arxiv.org/abs/1908.05627v1
• [stat.AP]Robust parametric modeling of Alzheimer’s disease progression
Mostafa Mehdipour Ghazi, Mads Nielsen, Akshay Pai, Marc Modat, M. Jorge Cardoso, Sébastien Ourselin, Lauge Sørensen
http://arxiv.org/abs/1908.05338v1
• [stat.ME]A grouped, selectively weighted false discovery rate procedure
Xiongzhi Chen, Sanat K. Sarkar
http://arxiv.org/abs/1908.05319v1
• [stat.ME]A hypothesis test of feasibility for external pilot trials assessing recruitment, follow-up and adherence rates
Duncan T. Wilson, Rebecca E. A. Walwyn, Julia Brown, Amanda J. Farrin
http://arxiv.org/abs/1908.05562v1
• [stat.ME]False Discovery Rate for Functional Data
Niels Lundtorp Olsen, Alessia Pini, Simone Vantini
http://arxiv.org/abs/1908.05272v1
• [stat.ME]With Malice Towards None: Assessing Uncertainty via Equalized Coverage
Yaniv Romano, Rina Foygel Barber, Chiara Sabatti, Emmanuel J. Candès
http://arxiv.org/abs/1908.05428v1
• [stat.ML]A Bayesian Choice Model for Eliminating Feedback Loops
Gökhan Çapan, İlker Gündoğdu, Ali Caner Türkmen, Çağrı\ Sofuoğlu, Ali Taylan Cemgil
http://arxiv.org/abs/1908.05640v1
• [stat.ML]Combining Prediction Intervals on Multi-Source Non-Disclosed Regression Datasets
Ola Spjuth, Robin Carrión Brännström, Lars Carlsson, Niharika Gauraha
http://arxiv.org/abs/1908.05571v1
• [stat.ML]End-to-End Learning from Complex Multigraphs with Latent Graph Convolutional Networks
Floris Hermsen, Peter Bloem, Fabian Jansen, Wolf Vos
http://arxiv.org/abs/1908.05365v1
• [stat.ML]Maximum Relevance and Minimum Redundancy Feature Selection Methods for a Marketing Machine Learning Platform
Zhenyu Zhao, Radhika Anand, Mallory Wang
http://arxiv.org/abs/1908.05376v1
• [stat.ML]Mixed pooling of seasonality in time series pallet forecasting
Hyunji Moon, Hyeonseop Lee
http://arxiv.org/abs/1908.05339v1
• [stat.ML]Optimizing Ensemble Weights and Hyperparameters of Machine Learning Models for Regression Problems
Mohsen Shahhosseini, Guiping Hu, Hieu Pham
http://arxiv.org/abs/1908.05287v1
• [stat.ML]Sequential Computer Experimental Design for Estimating an Extreme Probability or Quantile
Hao Chen, William J. Welch
http://arxiv.org/abs/1908.05357v1
• [stat.ML]Uplift Modeling for Multiple Treatments with Cost Optimization
Zhenyu Zhao, Totte Harinen
http://arxiv.org/abs/1908.05372v1